VIIRS Satellite Thermal Hotspots Map: Real-Time Fire Detection from NASA & NOAA

Track Active Fires and Thermal Anomalies Worldwide with Live Satellite Data

Satellite technology has revolutionized our ability to detect and monitor fires, volcanic activity, and thermal anomalies across the globe. Our VIIRS Thermal Hotspots Map provides real-time access to thermal detection data from NASA and NOAA satellites, offering unprecedented visibility into active fire locations, intensity measurements, and heat sources worldwide.

Whether you are a fire management professional, environmental researcher, agricultural monitor, or concerned citizen tracking wildfire threats, this interactive satellite fire detection tool delivers authoritative data directly from space-based sensors orbiting Earth every day.

What is the VIIRS Thermal Hotspots Map?

The VIIRS Thermal Hotspots Map is a free, interactive web application that visualizes thermal anomalies detected by the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard NASA and NOAA polar-orbiting satellites. This powerful tool displays active fire detections, volcanic thermal activity, gas flares, and other significant heat sources detected from space.

Key Features of Our Satellite Fire Detection System

Real-Time Satellite Data Integration

• Live thermal anomaly detections from VIIRS sensors
• Data from both Suomi-NPP and NOAA-20 satellites
• Multiple daily satellite passes for comprehensive coverage
• Near-real-time data updates (within 3-6 hours of detection)

Comprehensive Thermal Information

• Brightness temperature measurements (Kelvin)
• Fire Radiative Power (FRP) calculations in megawatts
• Detection confidence levels (low, nominal, high)
• Precise geographic coordinates for each hotspot
• Satellite acquisition date and time stamps

Advanced Visualization Tools

• Color-coded markers by confidence level
• Temperature gradient visualization option
• Interactive marker clustering for high-density areas
• Detailed pop-up information for each detection
• Responsive map interface for all devices

Data Export Capabilities

• Export thermal detections as GeoJSON for GIS analysis
• Download CSV files for spreadsheet processing
• Integration-ready formats for research applications
• Complete attribute data in all exports

Real-Time Statistics Dashboard

• Total hotspot count
• Average and maximum brightness temperatures
• High-confidence detection count
• Average Fire Radiative Power
• Last data update timestamp

Where Does the VIIRS Thermal Detection Data Come From?

Primary Data Source: NASA FIRMS and NOAA Satellites

Our thermal hotspots map pulls data directly from NASA’s Fire Information for Resource Management System (FIRMS), which distributes active fire and thermal anomaly data from multiple satellite sensors. The primary data comes from VIIRS instruments aboard two operational satellites.

VIIRS Instrument Specifications:

Suomi-NPP (Suomi National Polar-orbiting Partnership)

• Launched: October 2011
• Orbit: Polar, sun-synchronous at 824 km altitude
• Overpass times: Approximately 1:30 AM and 1:30 PM local time
• VIIRS spatial resolution: 375 meters at nadir
• Coverage: Global, twice daily

NOAA-20 (formerly JPSS-1)

• Launched: November 2017
• Orbit: Polar, sun-synchronous at 824 km altitude
• Overpass times: Approximately 1:30 AM and 1:30 PM local time (50 minutes offset from Suomi-NPP)
• VIIRS spatial resolution: 375 meters at nadir
• Coverage: Global, twice daily

How VIIRS Detects Thermal Anomalies

Detection Technology:

VIIRS uses thermal infrared channels to detect heat signatures that exceed background temperature thresholds:

Primary Detection Channels:

• I-4 (3.74 μm): Mid-infrared channel sensitive to high temperatures
• I-5 (11.45 μm): Thermal infrared for background temperature
• M-13 (4.05 μm): Additional mid-infrared confirmation

Detection Algorithm:

1. Background Temperature Assessment: Establish normal surface temperature
2. Anomaly Identification: Flag pixels exceeding temperature thresholds
3. Contextual Analysis: Compare the suspect pixel to the surrounding area
4. Confidence Assignment: Calculate detection certainty (low, nominal, high)
5. Attribute Calculation: Determine brightness temperature and FRP
6. Quality Control: Filter false detections and artifacts

What VIIRS Detects

Fire Sources:

• Active wildfires (vegetation fires)
• Agricultural burning (crop residue, clearing)
• Prescribed burns (controlled forest management)
• Structural fires (large enough to detect from space)
• Peat fires (underground smoldering fires)

Non-Fire Heat Sources:

• Active volcanic activity
• Gas flaring (oil and gas operations)
• Industrial facilities (steel mills, refineries)
• Large machinery operations
• Geothermal features

Data Processing and Distribution

NASA FIRMS Processing Pipeline:

1. Raw Data Reception: Satellite downlinks data to ground stations
2. Geolocation Processing: Precise coordinate calculation
3. Fire Detection Algorithm: Automated thermal anomaly identification
4. Attribute Calculation: Brightness, FRP, confidence determination
5. Quality Assurance: Automated and manual quality checks
6. Data Distribution: Near-real-time availability via web services

Data Latency:

• Near-real-time: 3-6 hours from satellite overpass
• Standard: Available within 12 hours
• Archive: Complete historical archive dating to 2012

Understanding the Data Limitations

Important Constraints and Considerations

While VIIRS provides exceptional fire detection capabilities, users must understand several important limitations:

Temporal Coverage Limitations

Satellite Overpass Frequency:

• Each satellite passes over any location twice daily (day and night)
• Combined, Suomi-NPP and NOAA-20 provide approximately 4 overpasses per day
• Polar regions receive more frequent coverage due to orbit convergence
• Equatorial regions have larger time gaps between observations

Detection Window:

• Fires must be active during satellite overpass to be detected
• Short-duration fires (under 2 hours) may be missed between passes
• Rapidly moving fires may appear as multiple detections along path
• Fire start time cannot be precisely determined from satellite data

Spatial Resolution and Detection Limits

Minimum Detectable Fire Size:

• Theoretical minimum: Varies with fire temperature and background conditions
• Practical minimum: 50-100 square meters for very hot fires
• Typical minimum: 1,000 square meters for moderate-intensity fires
• Cool, smoldering fires: May require several thousand square meters

Pixel Size Effects:

• 375-meter pixels can contain multiple small fires
• Cannot distinguish individual fires within the same pixel
• Edge-of-scan pixels are larger and less accurate
• Sub-pixel fires detected, but size underestimated

Atmospheric and Environmental Interference

Cloud Obscuration:

• Clouds block thermal infrared detection completely
• Smoke may reduce detection sensitivity
• Heavy haze can obscure smaller fires
• Cloud shadows can create false negatives

Solar Reflection:

• Daytime sun glint can interfere with detection
• Desert surfaces and bare rock can create false positives
• Snow and ice require different detection thresholds
• Urban heat islands may produce false detections

Terrain Effects:

• Mountains create shadows, affecting detection
• Canyons and valleys may have limited visibility
• A dense forest canopy can partially obscure ground fires
• Topographic slopes affect pixel footprint size

Confidence Level Interpretation

Low Confidence:

• May include false positives (sun glint, hot surfaces)
• Often includes smaller or cooler fires
• Use with caution for decision-making
• Valuable for detecting potential fires requiring investigation

Nominal Confidence:

• Moderate certainty of actual fire
• Represents typical fire detections
• Generally reliable for most applications
• Balance between sensitivity and accuracy

High Confidence:

• Very likely to be actual fires
• Large, hot fires with clear signatures
• Minimal false positive rate
• Most reliable for critical applications

Data Quality Considerations

Attribute Accuracy:

• Brightness Temperature: ±50-100 Kelvin, typical uncertainty
• Fire Radiative Power: ±30% uncertainty in most conditions
• Location: ±375 meters (one pixel) at nadir, worse at edges
• Time: Accurate to satellite overpass time (within seconds)

Known Issues:

• Gas flares frequently appear as persistent hotspots
• Industrial facilities may be detected daily
• Volcanic activity creates long-term thermal signatures
• Agricultural burning creates dense clusters of detections

What This Tool Should NOT Be Used For

⚠️ Critical Warning: This satellite thermal detection map shows fire activity but has important limitations. It should NOT be used for:

• Real-time firefighting decisions: Hours of delay between detection and data availability
• Determining if fires are currently active: Fire may have been extinguished since the satellite pass
• Precise fire perimeter mapping: 375-meter resolution is inadequate for detailed boundaries
• Detecting all fires: Smaller fires and those under clouds are missed
• Emergency evacuation decisions: Use official emergency management sources
• Fire behavior prediction: Data shows past detections, not future fire movement

For operational fire management and emergency information:

• Contact local fire management agencies
• Monitor official evacuation orders and warnings
• Use ground-based fire reports and observations
• Consult NIFC (National Interagency Fire Center) for US fires
• Check national fire agencies for other countries
• Access MODIS data for a longer historical perspective

This tool is best used for broad-scale fire monitoring, research applications, pattern analysis, and situational awareness, not tactical firefighting or immediate safety decisions.

How to Use the VIIRS Thermal Hotspots Map

Getting Started with Satellite Fire Detection

Step 1: Understanding the Display When you load the map, you will see thermal hotspots detected by VIIRS satellites within the last 24-48 hours:

• 🔴 Red markers = High confidence detections (very likely fires)
• 🟠 Orange markers = Nominal confidence (likely fires)
• 🟢 Green markers = Low confidence (possible fires or heat sources)

Step 2: Exploring Hotspot Details. Click any marker to view comprehensive detection information:

• Brightness temperature (Kelvin)
• Fire Radiative Power (megawatts)
• Confidence level
• Satellite acquisition date and time
• Geographic coordinates
• Satellite instrument source

Step 3: Interpreting the Data Use the statistics dashboard to understand fire activity patterns:

• Total number of detections in view
• Average brightness indicates typical fire intensity
• Maximum brightness shows most intense hotspot
• High-confidence count reveals likely active fires
• Average FRP indicates overall fire energy output

Advanced Features for Researchers

Temperature Visualization Enable the “Highlight High Temperature” option to emphasize extremely hot detections, helping identify the most intense fires or thermal anomalies.

Data Export Functions

GeoJSON Export:

• Geographic format compatible with QGIS, ArcGIS, and Google Earth
• Preserves all detection attributes
• Ready for spatial analysis and overlay operations
• Standard format for web mapping applications

CSV Export:

• Spreadsheet-compatible format
• Opens in Excel, Google Sheets, R, Python
• Ideal for statistical analysis
• Includes all numeric attributes and coordinates

Interpreting Fire Radiative Power (FRP)

What is FRP? Fire Radiative Power measures the rate of radiant heat energy released by a fire, expressed in megawatts (MW). Higher FRP values indicate more intense fires.

FRP Value Ranges:

• 0-50 MW: Small fires, agricultural burning, smoldering
• 50-200 MW: Moderate fires, active flaming
• 200-500 MW: Large, intense fires
• 500-1000 MW: Very large fires, extreme fire behavior
• 1000+ MW: Mega-fires, exceptional intensity

FRP Applications:

• Smoke emission estimation
• Fire intensity comparison
• Burned area prediction
• Fire behavior characterization
• Climate and atmospheric impact assessment

Understanding Brightness Temperature

Temperature Scales:

• Measurements in Kelvin (K)
• Water boils at 373K (100°C)
• Typical vegetation fire: 600-1000K
• Very intense fires: 1000-1500K
• Industrial sources: Varies widely

What Temperature Tells You:

• Higher temperatures indicate more intense combustion
• Very high values suggest dense fuel or multiple fires in a pixel
• Persistent moderate temperatures may indicate industrial sources
• Temperature combined with FRP provides fire characterization

Global Fire Monitoring Applications

Wildfire Management and Response

Fire Detection Benefits:

• Early detection of remote fires
• Monitoring fire spread and intensity
• Assessing fire behavior changes
• Validating ground reports
• Resource allocation support

Operational Use Cases:

• Pre-positioning firefighting resources
• Public information and awareness
• Evacuation planning support
• Post-fire damage assessment
• Historical fire pattern analysis

Agricultural Monitoring

Crop Residue Burning:

• Tracking agricultural fire activity
• Identifying burning hotspots
• Temporal pattern analysis
• Compliance monitoring for burn bans
• Regional agricultural practice assessment

Prescribed Fire Management:

• Monitoring controlled burn execution
• Assessing burn completeness
• Documenting prescribed fire activities
• Safety monitoring
• Environmental impact studies

Environmental and Climate Research

Biomass Burning Emissions:

• Carbon release calculations
• Smoke plume source identification
• Air quality impact assessment
• Climate forcing studies
• Atmospheric chemistry research

Ecosystem Monitoring:

• Fire regime characterization
• Vegetation fire frequency
• Habitat impact assessment
• Post-fire recovery studies
• Biodiversity threat analysis

Air Quality Management

Smoke Source Attribution:

• Identifying fire locations contributing to the smoke
• Regional air quality forecasting
• Health advisory trigger determination
• Transboundary pollution tracking
• Public health protection

PM2.5 and Particulate Prediction:

• Fire emissions estimation from FRP
• Smoke transport modeling inputs
• Real-time air quality monitoring
• Public exposure assessment

Volcanic Activity Monitoring

Thermal Anomaly Detection:

• Active lava flow identification
• Volcanic eruption monitoring
• Geothermal activity tracking
• Early warning system complement
• Scientific research applications

Oil and Gas Industry Monitoring

Gas Flare Detection:

• Persistent thermal signatures
• Regional flaring activity mapping
• Regulatory compliance monitoring
• Methane emission estimation
• Environmental impact assessment

Comparing VIIRS to Other Fire Detection Systems

VIIRS vs. MODIS

MODIS (Moderate Resolution Imaging Spectroradiometer):

• Operational: 2000-present (Terra and Aqua satellites)
• Spatial resolution: 1 kilometer
• Temporal resolution: 4 times daily
• Longer historical record

VIIRS Advantages:

• Higher spatial resolution (375m vs. 1km)
• Better small fire detection
• Improved nighttime detection
• Reduced false positives
• Modern instrument design

MODIS Advantages:

• Longer data record (since 2000)
• More research validation
• Wider user community
• Well-established processing algorithms

Recommendation: Use both systems together for comprehensive fire monitoring.

VIIRS vs. Landsat/Sentinel-2

Landsat and Sentinel-2:

• Very high spatial resolution (30m and 10m)
• Lower temporal resolution (8-16 days)
• Primarily for detailed post-fire analysis
• Limited active fire detection capability

VIIRS for Active Fire Detection:

• Near-real-time detection
• Multiple daily observations
• Optimized for thermal detection
• Global automated processing

Landsat/Sentinel-2 for Post-Fire Analysis:

• Detailed burned area mapping
• Vegetation recovery monitoring
• Fire severity assessment
• Precise perimeter delineation

VIIRS vs. Geostationary Satellites (GOES)

GOES Fire Detection:

• Continuous monitoring (every 5-15 minutes)
• Immediate fire detection
• Fire growth tracking
• Optimal for rapidly developing fires

VIIRS Advantages:

• Higher spatial resolution
• Better detection sensitivity
• More accurate location information
• Lower false alarm rate

GOES Advantages:

• No orbital gap periods
• Rapid-fire growth monitoring
• Real-time fire behavior tracking
• Continuous temporal coverage

VIIRS Data in Different Regions

North America

United States:

• Extensive wildfire monitoring across western states
• Agricultural burning in the Great Plains and the Southeast
• Prescribed fire tracking in national forests
• Integration with NIFC and state fire agencies

Canada:

• Boreal forest fire monitoring
• Remote northern fire detection
• Provincial fire service integration
• Air quality monitoring applications

Mexico:

• Agricultural burning detection
• Forest fire monitoring
• Air quality management
• Cross-border smoke impact assessment

South America

Amazon Basin:

• Deforestation fire detection
• Agricultural expansion monitoring
• Indigenous land protection
• International environmental monitoring

Cerrado and Gran Chaco:

• Savanna fire tracking
• Agricultural burning detection
• Land use change monitoring
• Biodiversity threat assessment

Africa

Sub-Saharan Africa:

• Extensive agricultural burning
• Savanna fire monitoring
• Pastoral burning practices
• Bushfire management

Central Africa:

• Tropical forest fires
• Agricultural clearing detection
• Peatland fire monitoring
• Conservation area protection

Southeast Asia

Indonesia and Malaysia:

• Peatland fire detection
• Plantation burning monitoring
• Transboundary haze tracking
• Air quality crisis management

Mainland Southeast Asia:

• Agricultural burning detection
• Forest fire monitoring
• Air quality impacts
• Regional cooperation support

Australia

Bushfire Monitoring:

• Early fire detection
• Fire spread tracking
• Resource deployment support
• Community warning systems

Northern Australia:

• Savanna burning programs
• Indigenous fire management
• Carbon abatement monitoring
• Biodiversity protection

Europe

Mediterranean Region:

• Summer wildfire monitoring
• Agricultural burning detection
• Forest fire management
• Cross-border coordination

Eastern Europe:

• Agricultural burning tracking
• Forest fire detection
• Air quality monitoring
• Peatland fire detection

Frequently Asked Questions (FAQ)

General Questions About VIIRS Thermal Detection

Q: How quickly does fire detection data become available after a satellite passes overhead?

A: VIIRS data typically becomes available 3-6 hours after the satellite overpass. The processing pipeline includes data downlink to ground stations, geolocation processing, fire detection algorithm execution, quality assurance, and distribution to various platforms. In some cases, data may be available within 2-3 hours, while in others it may take up to 12 hours depending on ground station availability and processing load.

Q: How often does VIIRS observe my location?

A: For most locations, VIIRS provides approximately 4 observations per day (2 from Suomi-NPP and 2 from NOAA-20), with one daytime and one nighttime pass from each satellite. However, the exact frequency varies by latitude. Polar regions receive many more overpasses due to orbit convergence, while equatorial regions may have slightly fewer observations. The timing of observations also varies daily as the satellites are in sun-synchronous orbits.

Q: Can VIIRS detect all fires?

A: No, VIIRS cannot detect all fires. The system misses fires that are:

• Too small (generally under 50-100 square meters, depending on intensity)
• Obscured by clouds or heavy smoke
• Not actively burning during satellite overpass
• Cool or smoldering with insufficient thermal signature
• Under dense forest canopy
• Occurring in the gap between satellite passes

VIIRS excels at detecting moderate to large active fires, but is not a complete inventory of all fire activity.

Q: What is the difference between VIIRS and MODIS fire detection?

A: VIIRS and MODIS are both satellite-based fire detection systems, but VIIRS is newer and more advanced:

• Spatial resolution: VIIRS 375m vs. MODIS 1km (VIIRS detects smaller fires)
• False alarm rate: VIIRS has fewer false detections
• Nighttime detection: VIIRS performs better at night
• Data record: MODIS has a longer history (2000-present) vs. VIIRS (2012-present)
• Satellites: VIIRS on Suomi-NPP and NOAA-20; MODIS on Terra and Aqua

For most current monitoring, VIIRS is preferred, but MODIS remains valuable for historical analysis.

Q: Why do I see thermal hotspots that are not fires?

A: VIIRS detects thermal anomalies, not exclusively fires. Common non-fire detections include:

• Gas flares: Oil and gas operations create persistent hotspots
• Volcanoes: Active lava and geothermal features
• Industrial facilities: Steel mills, refineries, power plants
• Solar reflection: Rare false positives from bright surfaces
• Hot surfaces: Desert rocks, bare soil in extreme heat

The confidence level helps distinguish true fires from other heat sources. High-confidence detections are very likely to be actual fires.

Q: Can I use this data for insurance claims or legal purposes?

A: VIIRS data can provide supporting evidence for the presence of fire activity in a general area and timeframe, but it has limitations for legal applications:

• Spatial resolution (375m) may not precisely identify specific properties
• Detection timing shows satellite overpass time, not fire start time
• Cloud cover may prevent the detection of actual fires
• Small fires may not be detected

For legal or insurance purposes, VIIRS data should be combined with ground-based reports, damage assessments, and official fire reports. Consult with legal professionals about the appropriate use of satellite data for your specific situation.

Questions About Fire Detection Accuracy

Q: How accurate is the location information for detected fires?

A: VIIRS location accuracy varies based on several factors:

• At nadir (directly below satellite): ±375 meters (one pixel)
• At scan edges: ±500-750 meters due to increased pixel size
• Terrain effects: Mountainous areas have additional geometric distortion
• Processing: Geolocation algorithm accuracy within specified limits

In most cases, the location is accurate enough to identify the general area of fire activity (within a few hundred meters), but it is not precise enough to identify specific structures or small property boundaries.

Q: What does the confidence level mean?

A: The confidence level represents the algorithm’s certainty that a detection is an actual fire:

Low Confidence:

• Higher probability of false positives
• May include sun glint, hot surfaces, or small fires
• Often, smaller or cooler thermal anomalies
• Use with caution and seek confirmation

Nominal Confidence:

• Moderate certainty of actual fire
• Typical for many fire detections
• Balance between sensitivity and specificity
• Generally reliable for most applications

High Confidence:

• Very high certainty of actual fire
• Large, hot fires with clear thermal signatures
• Minimal false positive rate
• Most reliable for operational decisions

In validation studies, high-confidence detections have over 90% accuracy for actual fires, while low-confidence detections may have 50-70% accuracy.

Q: Can VIIRS distinguish between different types of fires?

A: VIIRS cannot directly distinguish between wildfire, prescribed fire, agricultural burning, or other fire types based solely on the thermal detection. All appear as thermal anomalies. However, researchers and analysts can infer fire type based on:

• Location (forest vs. agricultural land vs. urban areas)
• Temporal patterns (regular agricultural burning vs. random wildfire)
• Cluster characteristics (single large fire vs. many small burns)
• Persistence (recurring industrial heat vs. temporary fire)
• Ancillary data (land cover, fire reports, news)

Fire management agencies often combine VIIRS data with ground reports, permits, and local knowledge to categorize fire types.

Q: How does cloud cover affect fire detection?

A: Clouds completely block thermal infrared detection. When clouds are present:

• Fires underneath are invisible to the satellite
• No detection occurs regardless of fire size or intensity
• Data gaps appear in cloudy regions
• Multiple days may pass without observation in persistently cloudy areas

During monsoon seasons or in tropical regions with frequent cloud cover, VIIRS may miss fire activity for extended periods. This is an inherent limitation of satellite-based thermal detection in the infrared spectrum.

Q: Are nighttime detections more or less accurate than daytime?

A: Nighttime detections often have some advantages:

• Lower background temperatures create stronger contrast
• No solar reflection interference
• Cooler ambient temperatures enhance thermal signatures
• Generally, fewer false positives

However, daytime detections benefit from:

• Better atmospheric conditions in many regions
• Multiple spectral channels for confirmation
• Higher satellite resolution in some bands

Overall, VIIRS performs well both day and night, with each having specific advantages. The confidence level accounts for time-of-day factors in the detection algorithm.

Questions About Fire Radiative Power (FRP)

Q: What does Fire Radiative Power (FRP) measure?

A: Fire Radiative Power quantifies the rate of radiant heat energy released by a fire, measured in megawatts (MW). It represents how much thermal energy the fire is emitting per unit time. Higher FRP values indicate:

• More intense fires
• Larger burning area within the pixel
• Higher fuel consumption rates
• Greater smoke and emission production

FRP is derived from the measured brightness temperature and the pixel area, providing a standardized measure of fire intensity that can be compared across different fires, locations, and times.

Q: How is FRP used in fire management and research?

A: FRP has numerous applications:

Operational Fire Management:

• Prioritizing firefighting resources (higher FRP = more intense fires)
• Comparing fire intensity between incidents
• Tracking fire behavior changes over time
• Identifying extreme fire behavior

Research Applications:

• Estimating smoke and particulate emissions
• Calculating biomass consumption
• Modeling air quality impacts
• Climate impact assessment
• Carbon cycle studies

Example: A fire with FRP of 500 MW is emitting significantly more energy and producing more smoke than a fire with FRP of 50 MW, even if both have the same area. This helps prioritize response and predict impacts.

Q: What is considered a high FRP value?

A: FRP interpretation depends on context:

Small Fires: 0-50 MW

• Agricultural burns
• Small wildland fires
• Smoldering fires
• Single-tree or grass fires

Moderate Fires: 50-200 MW

• Active wildland fires
• Moderate-intensity burning
• Typical managed burns
• Small structural fire clusters

Large Fires: 200-500 MW

• Large, intense wildfires
• Active crown fires
• Multiple structures burning
• High fuel consumption

Extreme Fires: 500-1000+ MW

• Mega-fires with extreme behavior
• Massive energy release
• Dangerous fire conditions
• Potentially catastrophic impacts

Individual VIIRS pixels rarely exceed 1,000-2,000 MW, but extreme fires can produce clusters of high-FRP detections.

Q: Can FRP be used to estimate smoke emissions?

A: Yes, FRP is directly related to smoke production and is commonly used in emission estimation:

FRP to Emissions:

• Higher FRP = higher fuel consumption rate
• Fuel consumption correlates with smoke production
• Emission factors convert FRP to particulate matter
• Real-time FRP enables near-real-time emission estimates

Applications:

• Air quality forecasting models
• Health advisory systems
• Smoke transport predictions
• Regulatory compliance monitoring

Many operational air quality models now incorporate VIIRS FRP data to improve smoke forecasts and particulate matter predictions.

Questions About Using the Data

Q: How can I download historical VIIRS data?

A: Historical VIIRS active fire data is available from multiple sources:

NASA FIRMS (Fire Information for Resource Management System):

• Web interface: firms.modaps.eosdis.nasa.gov
• Data download: Map area or by country
• Archive: Complete record since 2012
• Formats: Shapefile, KML, CSV, GeoJSON

NOAA CLASS (Comprehensive Large Array-data Stewardship System):

• Raw VIIRS data and processed products
• Requires registration
• Complete satellite data archive
• Various processing levels

NASA Earthdata:

• Multiple VIIRS products
• Scientific data formats (HDF, NetCDF)
• Requires Earthdata login
• Full archive access

For most users, NASA FIRMS provides the easiest access to processed fire detection data.

Q: Can I receive alerts when fires are detected in my area?

A: Yes, NASA FIRMS offers email and SMS fire alert services:

FIRMS Alert System:

• Define area of interest (polygon or radius)
• Receive notifications of new detections
• Configure alert frequency
• Free service

How to Set Up:

1. Visit the NASA FIRMS website
2. Create a free account
3. Draw the area of interest on the map
4. Configure alert parameters
5. Receive emails or SMS when fires are detected

This is particularly useful for fire managers, protected area monitoring, and personal property protection.

Q: What software can I use to analyze VIIRS data?

A: VIIRS fire data can be analyzed with various tools:

GIS Software:

• QGIS: Free, open-source (recommended for most users)
• ArcGIS: Commercial, powerful capabilities
• Google Earth Pro: Free, easy visualization
• GRASS GIS: Free, advanced spatial analysis

Programming Languages:

• Python: GeoPandas, Rasterio, Matplotlib for analysis and visualization
• R: sf, raster, ggplot2 packages for spatial analysis
• JavaScript: Leaflet, OpenLayers for web mapping

Spreadsheet Software:

• Excel: Basic analysis of CSV data
• Google Sheets: Collaborative data analysis
• LibreOffice Calc: Free spreadsheet option

Q: Is VIIRS data free to use?

A: Yes, VIIRS fire detection data is completely free and publicly available:

• No licensing fees
• No usage restrictions
• No registration required for basic access
• Public domain (US government data)

NASA and NOAA provide this data as a public service. You can use it for:

• Research and academic purposes
• Commercial applications
• Government operations
• Personal use
• Educational activities

Attribution to NASA FIRMS or NOAA is appreciated but not required.

Q: How do I export data from this map?

A: The map provides two export options:

GeoJSON Export:

1. Click the “Export GeoJSON” button
2. File downloads automatically
3. Open in GIS software (QGIS, ArcGIS, etc.)
4. Contains all attributes and geometry

CSV Export:

1. Click the “Export CSV” button
2. File downloads automatically
3. Open in Excel, Google Sheets, or statistical software
4. Contains latitude, longitude, and all attributes

Both formats include the complete dataset visible on the map, including brightness temperature, FRP, confidence level, acquisition time, and coordinates.

Questions About Technical Details

Q: What is the difference between VIIRS I-band and M-band data?

A: VIIRS has two types of spectral bands with different resolutions:

I-Bands (Imaging Bands):

• Higher spatial resolution: 375 meters
• Fewer spectral channels
• Used for active fire detection
• Better for small fire detection

M-Bands (Moderate Resolution Bands):

• Lower spatial resolution: 750 meters
• More spectral channels
• Used for various environmental products
• Complementary to I-band data

The fire detection shown on this map uses the I-band data (375m resolution) for optimal small fire detection capability.

Q: What is the scan angle, and how does it affect detection?

A: VIIRS scans perpendicular to the satellite track with a total swath width of approximately 3,000 km. The scan angle affects data quality:

At Nadir (directly below satellite):

• Best spatial resolution (375m)
• Smallest pixel size
• Highest accuracy

At Scan Edges (±56° from nadir):

• Degraded spatial resolution
• Larger pixel footprint (up to 2x larger)
• Increased geolocation uncertainty
• Viewing angle effects

The VIIRS fire detection algorithm accounts for scan angle effects, but detections near the scan edges have inherently higher uncertainty.

Q: How does VIIRS compare to other Earth observation missions?

A: VIIRS is part of a larger Earth observation constellation:

Polar-Orbiting Satellites:

• VIIRS: High-resolution, near-real-time fire detection
• MODIS: Longer record, lower resolution
• Landsat: Very high resolution, infrequent observations
• Sentinel-2: High resolution, 5-day revisit

Geostationary Satellites:

• GOES (US): Continuous monitoring, lower resolution
• Himawari (Japan): Asia-Pacific coverage, continuous
• Meteosat (Europe): European coverage, continuous

Each system has unique strengths, and combining multiple sources provides the most complete picture of fire activity.

Questions About Applications and Use Cases

Q: How is VIIRS data used for air quality management?

A: VIIRS fire detection is critical for air quality applications:

Smoke Source Identification:

• Pinpoint fire locations contributing to air pollution
• Attribute PM2.5 to specific fire events
• Track smoke plume origins

Emissions Estimation:

• FRP-based emission calculations
• Real-time particulate matter estimation
• Fuel consumption estimates

Forecasting:

• Input to air quality models (CMAQ, WRF-Chem)
• Smoke dispersion predictions
• Health advisory triggers

Example Application: When air quality monitors detect elevated PM2.5, VIIRS data helps identify whether fires are the source and where smoke is originating, enabling targeted health advisories.

Q: Can VIIRS data help with climate change research?

A: Yes, VIIRS fire data contributes to multiple aspects of climate research:

Biomass Burning Emissions:

• Carbon dioxide release calculations
• Methane and other greenhouse gas estimates
• Black carbon (soot) quantification
• Aerosol climate forcing

Fire Regime Changes:

• Long-term fire frequency trends
• Geographic shifts in fire patterns
• Fire season length changes
• Climate-fire relationships

Vegetation Dynamics:

• Post-fire ecosystem recovery
• Carbon sequestration impacts
• Land cover change monitoring
• Biodiversity effects

Feedback Loops:

• Fire-climate interactions
• Vegetation-fire-atmosphere coupling
• Albedo changes from fire

VIIRS provides consistent, long-term global fire observations essential for understanding fire’s role in the climate system.

Q: How do researchers validate VIIRS fire detections?

A: Validation uses multiple approaches:

Ground-Based Observations:

• Field crews verify detected fires
• Compare detection timing to fire reports
• Assess omission and commission errors

High-Resolution Imagery:

• Landsat and Sentinel-2 confirm fire scars
• Commercial satellite data (Planet, etc.)
• Aerial photography validation

Independent Fire Datasets:

• Compared to national fire databases
• Cross-validate with MODIS detections
• Check against news reports and social media

Statistical Analysis:

• Calculate detection rates by fire size
• Assess false alarm frequency
• Evaluate confidence level accuracy

Validation studies consistently show VIIRS high-confidence detections have over 90% accuracy, with the system detecting most fires larger than a few thousand square meters.

Q: What future improvements are planned for VIIRS fire detection?

A: Several enhancements are in development or planned:

Algorithm Improvements:

• Machine learning integration for reduced false positives
• Enhanced smoke penetration techniques
• Improved nighttime detection sensitivity
• Better volcanic/industrial heat filtering

Additional Satellites:

• NOAA-21 launched 2022 (JPSS-2)
• Future JPSS satellites planned through 2030s
• Increased temporal resolution with more satellites

Data Products:

• Sub-pixel fire characterization
• Improved FRP accuracy
• Fire size estimation algorithms
• Real-time fire progression tracking

Distribution Enhancements:

• Faster data latency (sub-hourly goal)
• Improved web services
• Mobile-friendly applications
• Enhanced alert systems

The goal is to provide even faster, more accurate fire information to support operational needs and research applications.

---

Leverage Satellite Technology for Fire Monitoring

The VIIRS Thermal Hotspots Map harnesses advanced satellite technology to provide unprecedented visibility into global fire activity. By accessing near-real-time thermal detections from space-based sensors, users gain valuable insights into fire patterns, intensity, and distribution across any region of the world.

For Fire Management Professionals:

• Early detection of remote fires
• Regional fire activity assessment
• Resource allocation support
• Fire behavior monitoring
• Historical pattern analysis

For Researchers and Scientists:

• Biomass burning quantification
• Emissions modeling inputs
• Climate impact studies
• Ecosystem monitoring
• Air quality research

For Environmental Managers:

• Protected area monitoring
• Deforestation tracking
• Agricultural burning assessment
• Regulatory compliance monitoring
• Conservation planning

For the Public:

• Wildfire awareness in your region
• Understanding fire patterns
• Air quality source identification
• Educational applications
• Environmental monitoring

Additional Resources:

• NASA FIRMS: firms.modaps.eosdis.nasa.gov
• NOAA VIIRS: nesdis.noaa.gov
• Fire Data Portal: earthdata.nasa.gov/firms
• VIIRS Information: jpss.noaa.gov/viirs.html

Bookmark this VIIRS thermal hotspots map and use it regularly to monitor fire activity in your region or areas of interest worldwide. Share this resource with colleagues, researchers, and anyone interested in understanding global fire patterns from space.

Data Source: NASA FIRMS and NOAA satellites. VIIRS thermal anomaly data provided by the Suomi-NPP and NOAA-20 satellites operated by NASA and NOAA. Data typically available 3-6 hours after satellite overpass.